<p dir="ltr">Ion mobility spectrometry (IMS), with its unparalleled ability to separate and filter ions based on their overall size before channeling them into a Mass Spectrometer, has placed itself as a cornerstone of the modern Analytical Chemistry field. IMS provides an orthogonal separation, aiding in the identification and analysis processes of various compounds. While there have been many inventions for ion mobility (IM) devices with exponential growth in the separation capability in the past few years, there is very little emphasis on the theoretical explanation. For example, most modern IMS devices often use a high ratio of electric field to gas concentration (E/n) as it provides better separation capabilities. However, the interaction between ion and gas at such E/n cannot be explained by current IM theories as they ignore several critical factors such as the increase in ion’s energy due to energetic collisions, the energy loss/transferred in the internal degree of freedoms, and change in the ion’s structure, requiring empirical data to identify ions after separation. The thesis presented here contributes towards bridging this gap by elucidating the complex interplay of forces and interactions that govern the ion separation process, thereby explaining on how these mechanisms can be further exploited for refined separation and advancing the computational approach to identify the separated ion.</p><p dir="ltr">To explain the ion-gas interaction under high E/n, this research extends the Two-Temperature Theory (2TT) up to the fourth order approximation. The central idea of the 2TT is to solve moments of the Boltzmann equation for the ion’s velocity distribution involving ion-gas collisions. The research shows a decreasing error between each subsequent approximations, indicating convergence. This advancement is demonstrated through the development and application of our in-house program, IMoS, and validated against experimental data for small ions in monoatomic gases. This research also justifies the mechanisms of increasing and decreasing mobility as the electric field is increased by explaining the interplay between the interaction potential and the collision energy.</p><p dir="ltr">Subsequent chapters investigate the impact of internal degrees of freedom (rotational and vibrational) on ion mobility. This includes pioneering work with the Structures for Lossless Ion Manipulations (SLIM) device to separate isotopomers, alongside computational advancements in simulating these effects, leading to the development of IMoS 2.0. In IMoS 2.0 software an ion is placed in a virtual drift tube with electric field, where it is free to rotate and translate upon collision. The research notably uncovers the role of rotational degrees of freedom in isotopomer separation, a previously underexplored area.</p><p dir="ltr">To ascertain the effect of the vibrational DoF and differentiate from the ion’s structural expansion and heating resulting from energetic collisions, a combined simulation of ion mobility and molecular dynamics (IM-MD) was performed. This analysis revealed that structural expansion plays a dominant role for the cause of deviation at high E/n, to such an extent that the vibrational DoF (or inelastic collisions) can normally be disregarded. Moreover, the research also indicates that using a combination of IM-MD simulation, one can identify accurate gas-phase structure of the ion at any temperature from a pool of probable structures.</p><p dir="ltr">Guided by these conclusions, the research now takes a significant step forward by aiming to accurately characterize protein structures in the gas phase using IM-MD simulation. Traditional MD simulations provide larger structures since the force field is not optimized for the gas-phase simulation. To address this, a biasing force towards the center of the protein is applied, compressing it. This method efficiently explores multiple feasible configurations, including those obscured by energy barriers. This strategy generated structures that closely align with the experimental evidence.</p>

<p dir="ltr">Mass spectrometry imaging (MSI) is a powerful technique for visualizing the distribution of molecules within biological samples. Advancements in MSI instrumentation and computational tools have enabled the impactful applications of this technique across various fields including clinical research, drug discovery, forensics, microbiology, and natural products. Nanospray desorption electrospray ionization (nano-DESI), an ambient localized liquid extraction ionization technique, has proven valuable to the MSI community. Nano-DESI has been used for imaging of various molecules in biological samples including drugs, metabolites, lipids, N-linked glycans, and proteins.</p><p dir="ltr">My research has been focused on expanding the sensitivity and specificity of nano-DESI for biomolecular imaging. One of the newly developed methods employs ammonium fluoride NH₄F as a solvent additive to enhance the sensitivity of nano-DESI for the analysis of lipids in negative ionization mode. Secondly, methods were developed for the spatial mapping of isobaric and isomeric species in biological tissues by implementing nano-DESI MSI on a triple quadrupole (QqQ) mass spectrometer. This work used multiple reaction monitoring (MRM) mode of a QqQ with unit mass resolution to separate isobaric lipid species that require high mass resolving power and imaging of isomeric low-abundance species in tissue sections. Next, I demonstrate nano-DESI as a liquid extraction technique for imaging of N-linked glycans within biological tissue sections. Lastly, the spatial distribution of eicosanoids and specialized pro-resolving mediators (SPMs) in a mouse model for acetaminophen-induced liver injury (AILI) provides insights into the inflammation and resolution phases of AILI. Collectively, these developments have advanced the sensitivity, chemical specificity, and molecular coverage of nano-DESI for imaging of different classes of molecules in biological tissues.</p>

<p dir="ltr">Atmospheric organic aerosols (OA) have diverse compositions and undergo complex reactions and transformations within the atmosphere, leading to profound impacts on air quality, climate, and atmospheric chemistry. In particular, these aerosols play an important role in Earth's effective radiative forcing (ERF) through interactions with solar radiation, absorbing and scattering sunlight and terrestrial radiation. These interactions result in a warming and cooling effect on the climate, respectively. This dissertation seeks to unravel the intricate molecular characteristics of atmospheric OA, focusing specifically on its light-absorbing components, known as ‘Brown Carbon’ (BrC), and aims to comprehend its dynamic interplay within the atmosphere. The research employs state-of-the-art multi-modal mass spectrometry techniques to investigate atmospheric OA derived from the combustion of fossil fuels and biomass burning. Through a combination of controlled laboratory experiments and real-world sample analyses, these works provide molecular-level insights crucial for source apportionment and predictive modeling of OA fate. Chapter 2 details the instrumentation and data analysis methods, laying a robust foundation for subsequent chapters.</p><p dir="ltr">Chapter 3 delves into the investigation of smoldering-phase biomass burning organic aerosols (BBOA) and introduces an innovative fractionation method for high-level molecular characterization, targeted to streamline source apportionment of BBOA. This chapter also presents an extensive assessment of particle-to-gas partitioning of BBOA, providing valuable information for modeling atmospheric lifetimes and fate. In Chapter 4, a comparative analysis of BBOA from wild and agricultural fires is conducted, employing advanced molecular characterization techniques. Chapter 5 showcases the synergistic use of multi-modal mass spectrometry techniques to probe the chemical evolution of individual BBOA components. Finally, Chapter 6 examines the molecular analysis of secondary OA (SOA) generated from the photooxidation of a fossil-fuel proxy.</p><p dir="ltr">The comprehensive molecular-level studies presented contribute essential insights for climate modeling, aiding in resolving uncertainties associated with OA's impact on global ERF. The research not only challenges existing analytical methods but also introduces novel approaches for obtaining relevant information about atmospheric OA components. Overall, this work advances our understanding of the intricate dynamics of atmospheric aerosols, facilitating more accurate climate predictions and addressing uncertainties surrounding their net radiative impact.</p>

<p><a></a><a></a><a></a><a></a><a></a><a></a><a></a><a></a><a></a><a></a><a>ABSTRACT</a></p> <p>Phenols are ubiquitous in our surroundings including biological molecules such as L-Dopa metabolites, food components, such as whiskey and liquid smoke, etc. This dissertation describes a new method for detecting phenols, by reaction with Gibbs reagent to form indophenols, followed by mass spectrometric detection. Unlike the standard Gibbs reaction which uses a colorimetric approach, the use of mass spectrometry allows for simultaneous detection of differently substituted phenols. The procedure is demonstrated to work for a large variety of phenols without <i>para</i>‐substitution. With <i>para</i>‐substituted phenols, Gibbs products are still often observed, but the specific product depends on the substituent. For <i>para</i> groups with high electronegativity, such as methoxy or halogens, the reaction proceeds by displacement of the substituent. For groups with lower electronegativity, such as amino or alkyl groups, Gibbs products are observed that retain the substituent, indicating that the reaction occurs at the <i>ortho</i> or <i>meta</i> position. In mixtures of phenols, the relative intensities of the Gibbs products are proportional to the relative concentrations, and concentrations as low as 1 μmol/L can be detected. The method is applied to the qualitative analysis of commercial liquid smoke, and it is found that hickory and mesquite flavors have significantly different phenolic composition.</p> <p>In the course of this study, we used this technique to quantify major phenol derivatives in commercial products such as liquid smoke (catechol, guaiacol and syringol) and whiskey (<i>o</i>-cresol, guaiacol and syringol) as the phenol derivatives are a significant part of the aroma of foodstuffs and alcoholic beverages. For instance, phenolic compounds are partly responsible for the taste, aroma and the smokiness in Liquid Smokes and Scotch whiskies. </p> <p>In the analysis of Liquid Smokes, we have carried out an analysis of phenols in commercial liquid smoke by using the reaction with Gibbs reagent followed by analysis using electrospray ionization mass spectrometry (ESI-MS). This analysis technique allows us to avoid any separation and/or solvent extraction steps before MS analysis. With this analysis, we are able to determine and compare the phenolic compositions of hickory, mesquite, pecan and apple wood flavors of liquid smoke. </p> <p>In the analysis of phenols in whiskey, we describe the detection of the Gibbs products from the phenols in four different commercial Scotch whiskies by using simple ESI-MS. In addition, by addition of an internal standard, 5,6,7,8-tetrahydro-1-napthol (THN), concentrations of the major phenols in the whiskies are readily obtained. With this analysis we are able to determine and compare the composition of phenols in them and their contribution in the taste, smokey, and aroma to the whiskies.</p> <p>Another important class of phenols are found in biological samples, such as L-Dopa and its metabolites, which are neurotransmitters and play important roles in living systems. In this work, we describe the detection of Gibbs products formed from these neurotransmitters after reaction with Gibbs reagent and analysis by using simple ESI‐MS. This technique would be an alternative method for the detection and simultaneous quantification of these neurotransmitters. </p> <p>Finally, in the course of this work, we found that the positive Gibbs tests are obtained for a wide range of <i>para</i>-substituted phenols, and that, in most cases, substitution occurs by displacement of the <i>para</i>-substituent. In addition, there is generally an additional unique second-phenol-addition product, which conveniently can be used from an analytical perspective to distinguish <i>para</i>-substituted phenols from the unsubstituted versions. In addition to using the methodology for phenol analysis, we are examining the mechanism of indophenol formation, particularly with the <i>para</i>-substituted phenols. </p> <p>The importance of peptides to the scientific world is enormous and, therefore, their structures, properties, and reactivity are exceptionally well-characterized by mass spectrometry and electrospray ionization. In the dipeptide work, we have used mass spectrometry to examine the dissociation of dipeptides of phenylalanine (Phe), containing sulfonated tag as a charge carrier (Phe*), proline (Pro) to investigate their gas phase dissociation. The presence of sulfonated tag (SO₃^-) on the Phe amino acid serves as the charge carrier such that the dipeptide backbone has a canonical structure and is not protonated. Phe-Pro dipeptide and their derivatives were synthesized and analyzed by LCQ-Deca mass spectroscopy to get the fragmentation mechanism. To confirm that fragmentation path, we also synthesized dikitopeparazines and oxazolines from all combinations of the dipeptides. All these analyses were confirmed by isotopic labeling experiments and determination and optimization of structures were carried out using theoretical calculation. We have found that the fragmentation of Phe*Pro and ProPhe* dipeptides form sequence specific b₂ ions. In addition, not only is the ‘mobile proton’ involved in the dissociation process, but also is the ‘backbone hydrogen’ is involved in forming b₂ ions. </p> <p> </p>

<p>Urine-based biomarkers offer numerous advantages for clinical analysis, including non-invasive collection, a suitable sample source for longitudinal disease monitoring, a better screenshot of disease heterogeneity, higher sample volumes, faster processing times, and lower rejection rates and costs. They will be extremely useful in a clinical trial context, which can be applied alone or in combination with other methods as long as they demonstrate clear reproducibility across cohorts. While biofluids such as urine present enormous challenges with a wide dynamic range and extreme complex typically dominated by a few highly abundant proteins, we have demonstrated that the analytical issue can be efficiently addressed by focusing on extracellular vesicles (EVs), tiny packages released by all kinds of cells. These tiny packages contain different kinds of molecules from inside the cells. Here, we established a robust EV isolation and characterization platform to screen and validate Parkinson’s Disease (PD) and Renal Cell Carcinoma (RCC) biomarkers from urine. PD is a progressive neurological disorder affecting body movement because some brain cells stop producing dopamine. PD is often not diagnosed until it has advanced, making early detection crucial. We investigated urinary EVs from 138 individuals to enable early detection and found several proteins involved in PD development that could be biological indicators for early disease detection. Several biochemical techniques were applied to verify our findings. In the second project, we attempted to develop a novel diagnostic technique for early intervention of RCC. Here, we made our efforts to develop a quantitative method based on data-independent acquisition (DIA) mass spectrometry to analyze urinary EV phosphoproteomics for non-invasive RCC biomarker screening. Combined with our in-house EVtrap method for EV isolation and PolyMAC enrichment of phosphopeptides, we quantified 2,584 unique phosphosites. We observed unique upregulated phosphosites and pathways differentiating healthy control (HC), chronic kidney disease (CKD), low-grade, and high-grade clear cell RCC. These applications have a significant promise for early PD and RCC diagnosis and monitoring based on actual functional proteins with urine as the source. These studies might provide a viable path to developing urinary EV-based disease diagnosis.</p>

<p dir="ltr">Tandem mass spectrometry (MSⁿ) has become the most widely used analytical technique for the chemical characterization of unknown organic compounds in complex mixtures. It has led to the development of a large number of mass spectrometers with different mass analyzers as well as a wide array of ionization methods. This technique can be coupled with a diverse range of chromatography methods, such as gas chromatography (GC) and high-performance liquid chromatography (HPLC). Some of the primary strengths of MS include its great sensitivity, its versatility to seamlessly integrate with various chromatography techniques and its flexibility in the sense of access to different mass analyzers and different ionization methods. During MS experiments, analytes are evaporated and ionized and the resulting ions are separated based on their mass-to-charge (<i>m/z</i>) ratios and then detected. On the other hand, MSⁿ experiments involve isolating a specific ion of interest from all other ions and subjecting them to reactions such as collision-activated dissociation (CAD) or ion-molecule reactions. These reactions generate product ions that can be used to obtain structural information for the analyte. In addition, MSⁿ experiments can be used to generate and study the chemical properties of reaction intermediates, such as oxenium cations. </p><p dir="ltr">The mass spectrometer and the ionization source used to perform the research discussed in this thesis are described in Chapter 2. After this, the development of experiments involving ion-molecule reactions accompanied by collision-activated dissociation in a linear quadrupole ion trap is discussed, with the goals of differentiating the aziridine functionality from structurally related functional groups, such as the amino group and identifying aromatic aldehyde functionalities in protonated oxygen-containing monofunctional analytes. The integration of machine learning with mass spectral data has become an increasingly prevalent and valuable way to interpret data faster and more accurately without human bias than conventional manual approaches. Chapter 5 discusses combining machine learning-guided automated HPLC analysis coupled with MSⁿ experiments based on diagnostic ion-molecule reactions for the structural elucidation of unknown compounds. Finally, experimental and computational studies on the gas-phase reactivity of quinoline-based ground-state singlet oxenium cations are discussed.</p>